fixes
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@@ -3357,7 +3357,7 @@ class WanVideoSampler:
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if callback is not None:
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if recammaster is not None:
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callback_latent = (latent_model_input[:, :orig_noise_len].to(device) - noise_pred[:, :orig_noise_len].to(device) * t.to(device) / 1000).detach().permute(1,0,2,3)
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if phantom_latents is not None:
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elif phantom_latents is not None:
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callback_latent = (latent_model_input[:,:-phantom_latents.shape[1]].to(device) - noise_pred[:,:-phantom_latents.shape[1]].to(device) * t.to(device) / 1000).detach().permute(1,0,2,3)
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else:
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callback_latent = (latent_model_input.to(device) - noise_pred.to(device) * t.to(device) / 1000).detach().permute(1,0,2,3)
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+6
-1
@@ -180,6 +180,8 @@ class WanVideoDiffusionForcingSampler:
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has_ref = image_embeds.get("has_ref", False)
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vace_context = image_embeds.get("vace_context", None)
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vace_scale = image_embeds.get("vace_scale", None)
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if not isinstance(vace_scale, list):
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vace_scale = [vace_scale] * (steps+1)
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vace_start_percent = image_embeds.get("vace_start_percent", 0.0)
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vace_end_percent = image_embeds.get("vace_end_percent", 1.0)
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vace_seqlen = image_embeds.get("vace_seq_len", None)
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@@ -198,9 +200,12 @@ class WanVideoDiffusionForcingSampler:
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for i in range(len(vace_additional_embeds)):
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if vace_additional_embeds[i].get("has_ref", False):
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has_ref = True
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vace_scale = vace_additional_embeds[i]["vace_scale"]
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if not isinstance(vace_scale, list):
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vace_scale = [vace_scale] * (steps+1)
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vace_data.append({
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"context": vace_additional_embeds[i]["vace_context"],
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"scale": vace_additional_embeds[i]["vace_scale"],
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"scale": vace_scale,
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"start": vace_additional_embeds[i]["vace_start_percent"],
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"end": vace_additional_embeds[i]["vace_end_percent"],
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"seq_len": vace_additional_embeds[i]["vace_seq_len"]
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